The faculty in the Department of Computational Biology have expertise in computer science, genomics, systems biology, population genetics, neurobiology, and modeling. They apply these skills to a wide range of exciting problems in the life sciences.
The faculty are members of the Computational Biology graduate field, as well as several other graduate fields offering M.Sc. and Ph.D. degrees. The department also administers the Computational Biology undergraduate concentration within the Bachelor of Science degree in Biology.
A long history
The Department of Computational Biology has had a long history of association with biological statisticians, tracing back to the very first uses of computers in performing statistical analysis. The earliest roots trace to the Biometrics Unit within the Department of Plant Breeding, founded in 1947. In 1948 Walter T. Federer was hired as its first faculty along with a secretary and a technical assistant; they were provided with (at that time) state-of-the-art Monroe and Marchant desk calculators.
1950s & 1960s
The department continued to grow from the mid 1950's through the 1960's, increasing both the number of faculty and the scope of its research. In 1966, the status of the Biometrics Unit was recognized in the renamed Department of Plant Breeding and Biometry and in 1998, the Unit became the Department of Biometrics, affiliated with the Department of Statistical Science, with seven full-time faculty.
The Biometrics unit
The Biometrics Unit and later the Department of Biometrics had a distinguished record in research, including Walter Federer, Shayle Searle, Charles McCulloch and George Casella as faculty. A report on the first 40 years of the unit lists 1041 technical reports, 546 papers, 21 books and 132 theses written. From the very beginning, the Unit had a strong service element providing statistical consulting to faculty and graduate students throughout Cornell University; this tradition continues to this day.
The Department of Biological Statistics & Computational Biology
In 2000, the Department of Biometry was reformulated as the Department of Biological Statistics and Computational Biology in order to incorporate the new and rapidly expanding field of quantitative and evolutionary genomics.
As of 2008, four new faculty have joined the department in the graduate field of Computational Biology and have established links with the Weill Medical School, the New Life Sciences Initiative and the Institute for Cell Biology.
Statistics & Data Science
In 2019, the department lost its statisticians to the new Department of Statistics and Data Science, retaining some members as joint faculty, and of course retaining a vibrant set of active collaborations. At this same time, the Department of Computational Biology was formed, with promise to grow in exciting new directions. Since then two junior faculty members were tenured, and we have hired two new faculty.
Frequently asked questions
Broadly speaking, computational biology is the application of computer science, statistics, and mathematics to problems in biology. Computational biology spans a wide range of fields within biology, including genomics/genetics, biophysics, cell biology, neurobiology, biochemistry, and evolution. Likewise, it makes use of tools and techniques from many different quantitative fields, including algorithm design, machine learning, Bayesian and frequentist statistics, and statistical physics.
Much of computational biology is concerned with the analysis of molecular data, such as biosequences (DNA, RNA, or protein sequences), three-dimensional protein structures, gene expression data, or molecular biological networks (metabolic pathways, protein-protein interaction networks, or gene regulatory networks). A wide variety of problems can be addressed using these data, such as the identification of disease-causing genes, the reconstruction of the evolutionary histories of species, and the unlocking of the complex regulatory codes that turn genes on and off. Computational biology can also be concerned with non-molecular data, such as brain imaging, electrophysiological, clinical or ecological data.
The terms computational biology and bioinformatics are often used interchangeably. However, computational biology sometimes connotes the development of algorithms, mathematical models, and methods for statistical inference, while bioinformatics is more associated with the development of software tools, databases, and visualization methods.
Undergraduates at Cornell who wish to focus on computational biology can do so through the Statistical Genomics concentration in the Biometry major, the Computational Biology concentration in the Biology major, or the Mathematical Biology concentration in the Mathematics major. These programs all differ somewhat in their requirements and areas of emphasis. Several undergraduate courses in computational biology are offered through these and other programs at Cornell.
Most graduate students interested in computational biology enroll in the Computational Biology Graduate Field. There is also a field of Computational BIology and Medicine, which is run jointly with faculty from the Weill Medical College, Rockefeller University and Sloan Kettering. However, it is also possible to do research in computational biology from graduate fields such as Genetics, Genomics and Development, Statistics, Applied Mathematics, and Computer Science. Many CB faculty members belong to these graduate fields as well as to Computational Biology.